Moving from Mapping Customer Journeys to Guiding Them

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Optimizing customer experience with precision, scale and in an economically feasible way is a struggle. However, with the right data, analytics and interaction capabilities, customer journeys can be mapped, significant events can be predicted, and interactions can be poised and used to guide each customer to the optimal destination in an automated, "always on" system. When done right, customer satisfaction and revenue go up, while marketing and customer care costs go down.

At this year’s Teradata Analytics Universe event, I held a session explaining the value of mapping customer journeys and how it’s possible to do so accurately and efficiently, even in a B2C industry.

I began my session by explaining the fundamental differences between a ‘customer journey’ and a ‘customer journey map’. The customer journey is the sum of experiences a customer has as they interact with your company and brand. Meanwhile, a customer journey map is a visual representation of every experience your customers have as they interact with your brand. It helps to tell the story of a customer´s experience with your company, from their original engagement, until they transact with you, and then ongoing into, hopefully, a long-term relationship.

Customer journey mapping comes out of the B2B industry where there are only thousands of customers, not millions like in the B2C market. Customer mapping in the B2B market from the first to the last customer touchpoint is relatively short. Some have tried to convert customer journey mapping to work in B2C marketing, but it doesn’t always translate.

One of the challenges of journey mapping is that it is a backwards view because it looks how people have transacted with you in the past. So it’s more representative in B2B, where there are only a few paths for customers to take. In B2C marketing, because of the elevated number of customers and channel tools, the journey would require an enormous number of maps. In addition, all of those maps do not identify the reasons for the mapped behaviours. As a result, these maps are not as actionable as they could be.

Understanding the customer’s mission

A company’s marketing should match its customer’s mission and what they are trying to do. For this reason, marketing should try to engage with customers during their current journey, without making up a new one from scratch. This is complicated by the fact that customers have more than one journey and mission with your company, they interact with your brand in many different ways and, as a consequence, there is no single map of a journey for each customer. So how can we know today’s mission, given that every customer’s mission is different, and each customer could have more than one mission?

Instead of drawing things on a white board, journeys are trackable with data. You can identify the journey using data and analytics, for example, with Teradata’s new analytics platform, Teradata Vantage. Capturing data nowadays has become a lot easier. Most companies keep track of data points including transaction records, website visits, mobile taps, social posts, and store and branch visits. If we take data from what the customer does and overlay what the company does on top of that, then take the marketing touchpoints and overlay those, we can begin see a lot more cause and effect with each step of the journey. This is a better approach than mapping a theoretical journey on a wall, because you have quantifiable data.

In a digital environment, the idea is to really fill in those interactions between transactions, because those interactions represent “intent”. The intention for the customer leading to engagement is really important, because each customer mission will have a different purpose, so companies need to have different styles of engagement, to match those objectives.

The other thing that makes this a little complicated is that customers might have different online IDs for the different platforms. An identity registry approach can link specific channel IDs to build a customer profile over time. In conjunction, paid media impressions and data from management platforms can be overlaid in order to understand the advertisements people respond to, how much is being spent on paid media, and begin to try to shape and steer these customer journeys.

Journey management must include non-digital channels, such as brick-and-mortar stores; it is very important to understand if the customer can make that as part of the mission or journey. It is important to know if a customer researches online and then buys in the store, or if a customer researches online, researches in the store, leaves, comes back and then buys. These are all clues of how many touchpoints a potential customer has with the brand before they ultimately convert.

Many technologies and ideas can lead the customer to leave some of their digital footprints, such as encouraging customers to ‘check-in’ using apps and social media, or gamification to boost interactivity with your brand.

Take action from your data

The digital form of journey mapping is “path analysis” – once you’ve tracked that people are transacting and interacting, you can start to understand the touches they have with the brand and digital format. This used to require a separate type of analytics that you had to buy, but now it’s built in to the Teradata Vantage platform; so all Teradata users now have access to this function.

Through path analysis it shows the touches a customer has with the brand and whether they are on a dominant path to transaction, or a less common path, but still show clues on how they interact with the brand, how they use products and behavioural segmentation. Path analysis gives the company clues also about the post-transactions between customer and brand so “what happens next” – so you can get ahead of the journey.

Once you understand your customers’ missions and the touchpoints on their journey, marketers can guide consumers with the next best interaction along the journey. Instead of mapping the past, you can map the current and predict the future journeys: where does the customer want to go next? You can make a win-win situation and you can find the answers in the data.